| // |
| // Copyright © 2022 Arm Ltd and Contributors. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #include "RefFullyConnectedWorkload.hpp" |
| |
| #include "FullyConnected.hpp" |
| #include "RefWorkloadUtils.hpp" |
| |
| #include "Profiling.hpp" |
| |
| namespace armnn |
| { |
| |
| unsigned int GetNumActivations(const TensorInfo& inputInfo) |
| { |
| unsigned int numActivations = 1; // Total number of activations in the input. |
| for (unsigned int i = 1; i < inputInfo.GetNumDimensions(); i++) |
| { |
| numActivations *= inputInfo.GetShape()[i]; |
| } |
| return numActivations; |
| } |
| |
| |
| RefFullyConnectedWorkload::RefFullyConnectedWorkload( |
| const FullyConnectedQueueDescriptor& descriptor, const WorkloadInfo& info) |
| : RefBaseWorkload<FullyConnectedQueueDescriptor>(descriptor, info) |
| , m_InputShape(info.m_InputTensorInfos[0].GetShape()) |
| , m_WeightShape(info.m_InputTensorInfos[1].GetShape()) |
| , m_OutputShape(info.m_OutputTensorInfos[0].GetShape()) |
| , m_NumActivations(GetNumActivations(info.m_InputTensorInfos[0])) |
| { |
| } |
| |
| void RefFullyConnectedWorkload::Execute() const |
| { |
| Execute(m_Data.m_Inputs, m_Data.m_Outputs); |
| } |
| |
| void RefFullyConnectedWorkload::ExecuteAsync(ExecutionData& executionData) |
| { |
| WorkingMemDescriptor* workingMemDescriptor = static_cast<WorkingMemDescriptor*>(executionData.m_Data); |
| Execute(workingMemDescriptor->m_Inputs, workingMemDescriptor->m_Outputs); |
| } |
| |
| void RefFullyConnectedWorkload::Execute(std::vector<ITensorHandle*> inputs, std::vector<ITensorHandle*> outputs) const |
| { |
| ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefFullyConnectedWorkload_Execute"); |
| |
| std::unique_ptr<Decoder<float>> inputDecoder = MakeDecoder<float>(GetTensorInfo(inputs[0]), inputs[0]->Map()); |
| std::unique_ptr<Encoder<float>> OutputEncoder = MakeEncoder<float>(GetTensorInfo(outputs[0]), outputs[0]->Map()); |
| |
| std::unique_ptr<Decoder<float>> weightsDecoder = MakeDecoder<float>(GetTensorInfo(inputs[1]), inputs[1]->Map()); |
| std::unique_ptr<Decoder<float>> biasDecoder; |
| |
| if (m_Data.m_Parameters.m_BiasEnabled) |
| { |
| biasDecoder = MakeDecoder<float>(GetTensorInfo(inputs[2]), inputs[2]->Map()); |
| } |
| |
| FullyConnected(m_InputShape, |
| *inputDecoder, |
| m_OutputShape, |
| *OutputEncoder, |
| m_WeightShape, |
| *weightsDecoder, |
| biasDecoder.get(), |
| m_Data.m_Parameters.m_BiasEnabled, |
| m_NumActivations, |
| m_Data.m_Parameters.m_TransposeWeightMatrix); |
| } |
| |
| } //namespace armnn |